Results 161 to 170 of about 6,127 (265)

Spatial variation in morphological traits of natural Haloxylon ammodendron populations on the eastern margin of the Badain Jaran Desert

open access: yesPlant Biology, EarlyView.
Natural Haloxylon ammodendron populations on the eastern margin of the Badain Jaran Desert showed size‐associated differences in plant height, crown diameter, and spatial patterns among stem‐base diameter classes. These patterns describe morphological spatial variation but do not establish specific environmental drivers.
S. Hongfei, W. Chengjie, L. Shijie
wiley   +1 more source

Poetic Sociology

open access: yesSociological Forum, EarlyView.
ABSTRACT Can sociologists feel? Sociological writing can be beautiful, making us think differently about people, processes, and structures. Yet traditional academic writing that does this is rare. For example, most articles adhere to a jargon‐filled format and structure that mimics a detached and disciplined writer.
Victoria Reyes
wiley   +1 more source

On the formation of superparamagnetic iron oxide nanoclusters. [PDF]

open access: yesRSC Adv
Schwarz P   +4 more
europepmc   +1 more source

Dyssynchrony without dysfunction: Left bundle branch block does not acutely reduce cardiac output

open access: yesThe Journal of Physiology, EarlyView.
Abstract figure legend Six electromechanical in silico heart models were simulated under healthy and pure acute left bundle branch block (LBBB) conditions. LBBB induced electrical dyssynchrony and increased left ventricular free wall strain, while the right and left ventricular ejection fraction remained relatively unchanged.
Carola Kruthoff   +6 more
wiley   +1 more source

The dose divided. [PDF]

open access: yesPalliat Support Care
Zieneldien T.
europepmc   +1 more source

fMRI signals of pattern separation in the neocortex and hippocampus to non-meaningful objects and their spatial location. [PDF]

open access: yesImaging Neurosci (Camb)
Nemecz Z   +7 more
europepmc   +1 more source

Symptom‐Based Machine Learning Framework for Early Syndrome Coronavirus 2 (SARS‐CoV‐2) Infection Prediction

open access: yesApplied AI Letters, Volume 8, Issue 1, February 2027.
This graphical abstract illustrates a symptom‐based machine learning framework for early prediction of SARS‐CoV‐2 infection. Clinical inputs such as SpO2, fever, cough, fatigue, and comorbidities are collected and preprocessed, followed by feature selection using a random forest‐based recursive elimination method.
Abdul Manan Koli   +9 more
wiley   +1 more source

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